| Name | Rlfap_mini/Rlfap-opt_mini/ Rlfap-ext-scen-11-opt_c18.xml |
| MD5SUM | ca82bc0dd04246bcda0d395b71fb38c4 |
| Bench Category | COP (optimization problem) |
| Best result obtained on this benchmark | SAT |
| Best value of the objective obtained on this benchmark | 22 |
| Best CPU time to get the best result obtained on this benchmark | 2520.05 |
| Satisfiable | |
| (Un)Satisfiability was proved | |
| Number of variables | 680 |
| Number of constraints | 4103 |
| Number of domains | 5 |
| Minimum domain size | 6 |
| Maximum domain size | 44 |
| Distribution of domain sizes | [{"size":6,"count":2},{"size":22,"count":10},{"size":24,"count":4},{"size":36,"count":336},{"size":44,"count":328}] |
| Minimum variable degree | 2 |
| Maximum variable degree | 63 |
| Distribution of variable degrees | [{"degree":2,"count":1},{"degree":4,"count":26},{"degree":5,"count":13},{"degree":6,"count":86},{"degree":7,"count":20},{"degree":8,"count":89},{"degree":9,"count":12},{"degree":10,"count":87},{"degree":11,"count":28},{"degree":12,"count":42},{"degree":13,"count":25},{"degree":14,"count":40},{"degree":15,"count":14},{"degree":16,"count":40},{"degree":17,"count":8},{"degree":18,"count":29},{"degree":19,"count":6},{"degree":20,"count":18},{"degree":21,"count":13},{"degree":22,"count":11},{"degree":23,"count":7},{"degree":24,"count":7},{"degree":25,"count":8},{"degree":26,"count":8},{"degree":28,"count":9},{"degree":29,"count":8},{"degree":30,"count":2},{"degree":31,"count":6},{"degree":32,"count":1},{"degree":36,"count":3},{"degree":37,"count":3},{"degree":39,"count":2},{"degree":40,"count":2},{"degree":43,"count":1},{"degree":44,"count":1},{"degree":45,"count":1},{"degree":48,"count":1},{"degree":56,"count":1},{"degree":63,"count":1}] |
| Minimum constraint arity | 2 |
| Maximum constraint arity | 2 |
| Distribution of constraint arities | [{"arity":2,"count":4103}] |
| Number of extensional constraints | 4103 |
| Number of intensional constraints | 0 |
| Distribution of constraint types | [{"type":"extension","count":4103}] |
| Optimization problem | YES |
| Type of objective | min NVALUES |
| Solver Name | TraceID | Answer | objective function | CPU time | Wall clock time |
|---|---|---|---|---|---|
| cosoco 1.12 (complete) | 4298203 | SAT (TO) | 22 | 2520.05 | 2519.9 |
| MiniCPFever 2018-04-29 (complete) | 4298205 | ? (NS) | 3.85809 | 1.70952 | |
| Solver of Xavier Schul & Yvhan Smal 2018-04-28 (incomplete) | 4298207 | ? (NS) | 4.69043 | 2.0207 | |
| SuperSolver_Macq_Stevenart 2018-04-27 (incomplete) | 4298208 | ? (NS) | 4.78305 | 1.9964 | |
| The dodo solver 2018-04-29 (complete) | 4298209 | ? (NS) | 4.94944 | 2.18582 | |
| GG's minicp 2018-04-29 (complete) | 4298204 | ? (NS) | 5.9756 | 3.12643 | |
| slowpoke 2018-04-29 (incomplete) | 4298206 | ? (NS) | 15.7856 | 5.017 |
This section presents information obtained from the best job displayed in the list (i.e. solvers whose names are not hidden).
objective function: 22<instantiation type='solution' cost='22'> <list>x[0] x[100] x[101] x[102] x[103] x[104] x[105] x[106] x[107] x[108] x[109] x[10] x[110] x[111] x[112] x[113] x[114] x[115] x[116] x[117] x[118] x[119] x[11] x[120] x[121] x[122] x[123] x[124] x[125] x[126] x[127] x[128] x[129] x[12] x[130] x[131] x[132] x[133] x[134] x[135] x[136] x[137] x[138] x[139] x[13] x[140] x[141] x[142] x[143] x[144] x[145] x[146] x[147] x[148] x[149] x[14] x[150] x[151] x[152] x[153] x[154] x[155] x[156] x[157] x[158] x[159] x[15] x[160] x[161] x[162] x[163] x[164] x[165] x[166] x[167] x[168] x[169] x[16] x[170] x[171] x[172] x[173] x[174] x[175] x[176] x[177] x[178] x[179] x[17] x[180] x[181] x[182] x[183] x[184] x[185] x[186] x[187] x[188] x[189] x[18] x[190] x[191] x[192] x[193] x[194] x[195] x[196] x[197] x[198] x[199] x[19] x[1] x[200] x[201] x[202] x[203] x[204] x[205] x[206] x[207] x[208] x[209] x[20] x[210] x[211] x[212] x[213] x[214] x[215] x[216] x[217] x[218] x[219] x[21] x[220] x[221] x[222] x[223] x[224] x[225] x[226] x[227] x[228] x[229] x[22] x[230] x[231] x[232] x[233] x[234] x[235] x[236] x[237] x[238] x[239] x[23] x[240] x[241] x[242] x[243] x[244] x[245] x[246] x[247] x[248] x[249] x[24] x[250] x[251] x[252] x[253] x[254] x[255] x[256] x[257] x[258] x[259] x[25] x[260] x[261] x[262] x[263] x[264] x[265] x[266] x[267] x[268] x[269] x[26] x[270] x[271] x[272] x[273] x[274] x[275] x[276] x[277] x[278] x[279] x[27] x[280] x[281] x[282] x[283] x[284] x[285] x[286] x[287] x[288] x[289] x[28] x[290] x[291] x[292] x[293] x[294] x[295] x[296] x[297] x[298] x[299] x[29] x[2] x[300] x[301] x[302] x[303] x[304] x[305] x[306] x[307] x[308] x[309] x[30] x[310] x[311] x[312] x[313] x[314] x[315] x[316] x[317] x[318] x[319] x[31] x[320] x[321] x[322] x[323] x[324] x[325] x[326] x[327] x[328] x[329] x[32] x[330] x[331] x[332] x[333] x[334] x[335] x[336] x[337] x[338] x[339] x[33] x[340] x[341] x[342] x[343] x[344] x[345] x[346] x[347] x[348] x[349] x[34] x[350] x[351] x[352] x[353] x[354] x[355] x[356] x[357] x[358] x[359] x[35] x[360] x[361] x[362] x[363] x[364] x[365] x[366] x[367] x[368] x[369] x[36] x[370] x[371] x[372] x[373] x[374] x[375] x[376] x[377] x[378] x[379] x[37] x[380] x[381] x[382] x[383] x[384] x[385] x[386] x[387] x[388] x[389] x[38] x[390] x[391] x[392] x[393] x[394] x[395] x[396] x[397] x[398] x[399] x[39] x[3] x[400] x[401] x[402] x[403] x[404] x[405] x[406] x[407] x[408] x[409] x[40] x[410] x[411] x[412] x[413] x[414] x[415] x[416] x[417] x[418] x[419] x[41] x[420] x[421] x[422] x[423] x[424] x[425] x[426] x[427] x[428] x[429] x[42] x[430] x[431] x[432] x[433] x[434] x[435] x[436] x[437] x[438] x[439] x[43] x[440] x[441] x[442] x[443] x[444] x[445] x[446] x[447] x[448] x[449] x[44] x[450] x[451] x[452] x[453] x[454] x[455] x[456] x[457] x[458] x[459] x[45] x[460] x[461] x[462] x[463] x[464] x[465] x[466] x[467] x[468] x[469] x[46] x[470] x[471] x[472] x[473] x[474] x[475] x[476] x[477] x[478] x[479] x[47] x[480] x[481] x[482] x[483] x[484] x[485] x[486] x[487] x[488] x[489] x[48] x[490] x[491] x[492] x[493] x[494] x[495] x[496] x[497] x[498] x[499] x[49] x[4] x[500] x[501] x[502] x[503] x[504] x[505] x[506] x[507] x[508] x[509] x[50] x[510] x[511] x[512] x[513] x[514] x[515] x[516] x[517] x[518] x[519] x[51] x[520] x[521] x[522] x[523] x[524] x[525] x[526] x[527] x[528] x[529] x[52] x[530] x[531] x[532] x[533] x[534] x[535] x[536] x[537] x[538] x[539] x[53] x[540] x[541] x[542] x[543] x[544] x[545] x[546] x[547] x[548] x[549] x[54] x[550] x[551] x[552] x[553] x[554] x[555] x[556] x[557] x[558] x[559] x[55] x[560] x[561] x[562] x[563] x[564] x[565] x[566] x[567] x[568] x[569] x[56] x[570] x[571] x[572] x[573] x[574] x[575] x[576] x[577] x[578] x[579] x[57] x[580] x[581] x[582] x[583] x[584] x[585] x[586] x[587] x[588] x[589] x[58] x[590] x[591] x[592] x[593] x[594] x[595] x[596] x[597] x[598] x[599] x[59] x[5] x[600] x[601] x[602] x[603] x[604] x[605] x[606] x[607] x[608] x[609] x[60] x[610] x[611] x[612] x[613] x[614] x[615] x[616] x[617] x[618] x[619] x[61] x[620] x[621] x[622] x[623] x[624] x[625] x[626] x[627] x[628] x[629] x[62] x[630] x[631] x[632] x[633] x[634] x[635] x[636] x[637] x[638] x[639] x[63] x[640] x[641] x[642] x[643] x[644] x[645] x[646] x[647] x[648] x[649] x[64] x[650] x[651] x[652] x[653] x[654] x[655] x[656] x[657] x[658] x[659] x[65] x[660] x[661] x[662] x[663] x[664] x[665] x[666] x[667] x[668] x[669] x[66] x[670] x[671] x[672] x[673] x[674] x[675] x[676] x[677] x[678] x[679] x[67] x[68] x[69] x[6] x[70] x[71] x[72] x[73] x[74] x[75] x[76] x[77] x[78] x[79] x[7] x[80] x[81] x[82] x[83] x[84] x[85] x[86] x[87] x[88] x[89] x[8] x[90] x[91] x[92] x[93] x[94] x[95] x[96] x[97] x[98] x[99] x[9] </list> <values>338 694 456 554 792 484 722 142 380 86 324 30 268 30 380 142 338 100 380 142 338 100 268 324 86 86 324 380 142 16 254 100 338 30 324 86 394 156 16 254 86 324 100 338 268 792 554 764 526 254 16 338 100 268 30 268 254 16 324 86 254 16 394 156 380 142 30 456 694 254 16 30 268 100 338 484 722 16 156 394 16 254 456 694 324 86 484 722 254 30 268 380 142 254 16 456 694 254 16 254 156 394 254 16 414 652 86 324 268 30 16 100 16 254 554 792 554 792 142 380 394 156 380 16 254 484 722 30 268 456 694 338 100 142 324 86 268 30 30 268 694 456 764 526 324 142 380 142 380 16 254 338 100 30 268 86 86 324 100 338 30 268 30 268 268 30 338 456 694 16 254 338 100 30 268 722 484 100 142 380 268 30 694 456 268 30 456 694 694 268 30 324 86 100 338 100 338 30 268 456 142 380 694 456 652 414 324 86 86 324 86 30 268 16 254 254 16 86 324 268 30 324 394 338 100 86 324 30 268 338 100 268 30 268 16 254 86 324 142 380 338 100 86 324 30 100 338 254 16 86 324 86 324 142 380 324 86 324 142 380 30 268 268 30 86 324 86 30 268 100 338 16 254 16 254 30 268 156 142 380 394 156 16 254 16 254 254 16 394 16 254 86 324 142 380 16 254 484 722 86 268 30 142 380 456 694 380 142 100 338 324 30 268 338 100 380 142 268 30 456 694 142 16 254 380 142 156 394 380 142 380 142 380 156 254 16 254 16 100 338 338 100 30 268 100 456 694 338 100 694 456 268 30 30 268 338 694 456 254 16 142 380 380 142 324 86 380 338 100 268 30 30 268 268 30 100 338 142 30 268 338 100 30 268 142 380 30 268 394 16 254 86 324 142 380 100 338 16 254 156 16 254 338 100 268 30 100 338 86 324 16 16 254 16 254 268 30 86 324 268 30 254 86 324 268 30 86 324 268 30 338 100 30 268 30 254 16 268 30 86 324 694 456 268 16 16 254 652 414 30 268 722 484 324 86 86 86 324 722 484 526 764 142 380 100 338 324 86 324 30 268 100 338 484 722 142 380 30 268 30 30 268 30 268 86 324 30 268 268 380 142 100 338 30 268 30 268 30 268 722 254 16 394 156 30 268 156 394 324 86 484 100 338 30 268 254 16 30 268 100 338 764 30 268 100 338 268 30 338 100 268 30 526 324 86 338 100 268 30 86 324 100 338 338 268 30 338 100 268 30 86 324 86 324 100 254 268 30 338 100 338 100 100 338 792 554 30 30 268 30 268 324 86 254 16 86 324 268 16 254 100 338 380 142 324 86 142 380 254 380 142 156 394 324 86 100 338 30 268 16 324 86 268 30 380 142 324 86 30 268 394 30 268 268 30 338 100 324 86 380 142 156 268 30 268 30 142 380 30 268 100 338 86 16 254 380 142 380 142 30 268 254 16 324 652 414 554 652 414 268 30 156 394 722 484 268 30 792 16 254 16 254 394 156 86 324 16 254 484 380 142 16 254 254 16 324 86 16 254 722 </values> </instantiation>